COM044000 books

Learn modern-day technologies from modern-day technical giants Key Features Real-world success and failure stories of artificial intelligence explained Understand concepts of artificial intelligence and deep learning methods Learn how to use artificial intelligence and deep learning methods Know how to prepare dataset and implement models using industry leading Python packages You’ll be able to apply and analyze the results produced by the models for prediction Description The aim of this book is to help the readers understand the concept of artificial intelligence and deep learning methods and implement them into their businesses and organizations. The first two chapters describe the introduction of the artificial intelligence and deep learning methods. In the first chapter, the concept of human thinking process, starting from the biochemical responses within the structure of neurons to the problem-solving steps through computational thinking skills are discussed. All chapters after the first two should be considered as the study of different technological and Artificial Intelligence giants of current age. These chapters are placed in a way that each chapter could be considered a separate study of a separate company, which includes the achievements of intelligent services currently provided by the company, discussion on the business model of the company towards the use of the deep learning technologies, the advancement of the web services which are incorporated with intelligent capability introduced by company, the efforts of the company in contributing to the development of the artificial intelligence and deep learning research. What You Will Learn How to use the algorithms written in the Python programming language to design models and perform predictions in general datasets Understand use cases in different industries related to the implementation of artificial intelligence and deep learning methods Learn the use of potential ideas in artificial intelligence and deep learning methods to improve the operational processes or new products and how services can be produced based on the methods Who this book is for This book is targeted to business and organization leaders, technology enthusiasts, professionals, and managers who seek knowledge of artificial intelligence and deep learning methods. Table of Contents 1. Artificial Intelligence and Deep Learning 2. Data Science for Business Analysis 3. Decision Making 4. Intelligent Computing Strategies By Google 5. Cognitive Learning Services in IBM Watson 6. Advancement web services by Baidu 7. Improved Social Business by Facebook 8. Personalized Intelligent Computing by Apple 9.Cloud Computing Intelligent by Microsoft About the Authors Dr. Jagreet Kaur is a doctorate in computer science and engineering. Her topic of thesis was “ARTIFICIAL INTELLIGENCE BASED ANALYTICAL PLATFORM FOR PREDICTIVE ANALYSIS IN HEALTH CARE.” With more than 12 years of experience in academics and research, she is working in data wrangling, machine learning and deep learning algorithms on large datasets, real-time data often in production environments for data science solutions and data products to get actionable insights for the last four years. Navdeep Singh Gill is a technology and solution architect having more than 15 years of experience in the IT and Telecom industry. For the past six years, he is working in big data analytics, automation and advanced analytics using machine learning and deep learning for planning and architecting of data science solutions and data products.

A Practicing Guide to TensorFlow and Deep Learning Key Features -Equipped with a necessary introduction to Deep Learning and AI. -Includes demos and templates to give your projects a good start. -Find more on the most important facets of AI, image, and speech recognition. Description This book begins with the configuration of an Anaconda development environment, essential for practicing the deep learning process. The basics of machine learning, which are needed for Deep Learning, are explained in this book. TensorFlow is the industry-standard library for Deep Learning, and thereby, it is covered extensively with both versions, 1.x and 2.x. As neural networks are the heart of Deep Learning, the book explains them in great detail and systematic fashion, beginning with a single neuron and progressing through deep multilayer neural networks. The emphasis of this book is on the practical application of key concepts rather than going in-depth with them. After establishing a firm basis in TensorFlow and Neural Networks, the book explains the concepts of image recognition using Convolutional Neural Networks (CNN), followed by speech recognition, and natural language processing (NLP). Additionally, this book discusses Transformers, the most recent advancement in NLP. What you will learn -Create machine learning models for classification and regression. -Utilize TensorFlow 1.x to implement neural networks. -Work with the Keras API and TensorFlow 2. -Learn to design and train image categorization models. -Construct translation and Q & A apps using transformer-based language models. Who this book is for This book is intended for those new to Deep Learning who want to learn about its principles and applications. Before you begin, you'll need to be familiar with Python. Table of Contents 1. Introduction to Artificial Intelligence 2. Machine Learning 3. TensorFlow Programming 4. Neural Networks 5. TensorFlow 2 6. Image Recognition 7. Speech Recognition

Learn how to process and analysis data using Python Key Features The book has theories explained elaborately along with Python code and corresponding output to support the theoretical explanations. The Python codes are provided with step-by-step comments to explain each instruction of the code. The book is not just dealing with the background mathematics alone or only the programs but beautifully correlates the background mathematics to the theory and then finally translating it into the programs. A rich set of chapter-end exercises are provided, consisting of both short-answer questions and long-answer questions. Description This book introduces the fundamental concepts of Data Science, which has proved to be a major game-changer in business solving problems. Topics covered in the book include fundamentals of Data Science, data preprocessing, data plotting and visualization, statistical data analysis, machine learning for data analysis, time-series analysis, deep learning for Data Science, social media analytics, business analytics, and Big Data analytics. The content of the book describes the fundamentals of each of the Data Science related topics together with illustrative examples as to how various data analysis techniques can be implemented using different tools and libraries of Python programming language. Each chapter contains numerous examples and illustrative output to explain the important basic concepts. An appropriate number of questions is presented at the end of each chapter for self-assessing the conceptual understanding. The references presented at the end of every chapter will help the readers to explore more on a given topic. What will you learn Perform processing on data for making it ready for visual plot and understand the pattern in data over time. Understand what machine learning is and how learning can be incorporated into a program. Know how tools can be used to perform analysis on big data using python and other standard tools. Perform social media analytics, business analytics, and data analytics on any data of a company or organization. Who this book is for The book is for readers with basic programming and mathematical skills. The book is for any engineering graduates that wish to apply data science in their projects or wish to build a career in this direction. The book can be read by anyone who has an interest in data analysis and would like to explore more out of interest or to apply it to certain real-life problems. Table of Contents 1. Fundamentals of Data Science1 2. Data Preprocessing 3. Data Plotting and Visualization 4. Statistical Data Analysis 5. Machine Learning for Data Science 6. Time-Series Analysis 7. Deep Learning for Data Science 8. Social Media Analytics 9. Business Analytics 10. Big Data Analytics About the Author Dr. Gypsy Nandi is an Assistant Professor (Sr) in the Department of Computer Applications, Assam Don Bosco University, India. Her areas of interest include Data Science, Social Network Mining, and Machine Learning. She has completed her Ph.D. in the field of ‘Social Network Analysis and Mining’. Her research scholars are currently working mainly in the field of Data Science. She has several research publications in reputed journals and book series. Dr. Rupam Kumar Sharma is an Assistant Professor in the Department of Computer Applications, Assam Don Bosco University, India. His area of interest includes Machine Learning, Data Analytics, Network, and Cyber Security. He has several research publications in reputed SCI and Scopus journals.

Leverage SharePoint Online Modern Experience to create beautiful, dynamic and mobile-ready sites and pages Description Lots of small, medium and large organizations or enterprises are using Office 365 for their business. And Microsoft is also investing heavily on Office 365 and providing lots of new features in Office 365 and other services in Office 365 like Office application or SharePoint Online, Yammer, Teams, Flow or PowerApps, etc. SharePoint is one of the popular portal technologies and web-based business collaboration and document management system. With Office 365 subscription, organizations can use SharePoint Online. Microsoft has announced the Modern features in SharePoint for a long time. Modern Experience is the future of SharePoint Online and on-premises also. This book is a comprehensive guide that lets you explore the Modern features in SharePoint Online or SharePoint Server 2019. In the book, I have covered details on Modern Team sites, communication sites, how you can customize the team sites according to your business requirement. You will also get hands-on Experience on how you can customize Modern site pages. I have also explained in detail various new features of Modern list and document libraries in SharePoint. This book also contains a few SharePoint portal examples, you will get in-depth knowledge on how to design team sites with various useful web parts. Few Organizations are still using SharePoint On-premises versions like SharePoint server 2019. I have also explained the Modern Experience in SharePoint 2019. Always it is better to know also, what are the things which are not possible in SharePoint Modern Experience, based on which you can check the impact, before moving to the SharePoint Online Modern Experience. Audience This book is for the site owners, power users or administrators who want to design attractive pages for SharePoint Modern team sites or publishing sites. Though the book is intended for SharePoint developer knowledge, but a little understanding of SharePoint is required. We have provided detailed steps with proper screenshots for references. This book is also for the developers who are trying to build pages for Modern SharePoint team sites or publishing site in SharePoint Online or SharePoint server 2019. What you will Learn In this book, you will learn what are Modern Experiences in SharePoint. How we can handle at the organizational level. What are the things which are not possible in SharePoint Online Modern Experience. Various new features of SharePoint Online Modern list and document libraries. You will also learn various web parts and how we can use those web parts while designing pages for your sites. Various examples of SharePoint Modern portal designs. How we can create and customize Modern site pages. How we can also start with SharePoint Server 2019 and use various Modern web parts in SharePoint 2019 sites. Key Features Learn how to use SharePoint Online Modern Experience (Modern UI) Create a Modern team site and communication site for your organization in SharePoint Online or SharePoint Server 2019 Effectively use Modern list and Libraries in SharePoint Online or SharePoint 2019 Learn about various Modern SharePoint web parts Create attractive and responsive portals in SharePoint Online or SharePoint 2019 Table of Contents Data Science Fundamentals Installing Software and Setting up Lists and Dictionaries Function and Packages NumPy Foundation Pandas and Dataframe Interacting with Databases Thinking Statistically in Data Science How to import data in Python? Cleaning of imported data Data Visualization Data Pre-processing Supervised Machine Learning Unsupervised Machine Learning Handling Time-Series Data Time-Series Methods Case Study – 1 Case Study – 2 Case Study – 3 Case Study – 4 About the Author Bijaya is a Microsoft MVP (Office Servers & Services) and having more than 11 years of experience in Microsoft Technologies specialized in SharePoint. He is Co-founder of TSInfo Technologies, a SharePoint consulting, training & development company in Bangalore, India. He has been a technology writer for many years and writes many SharePoint articles on his websites SharePointSky.com and EnjoySharePoint.com. Bijaya is a passionate individual who loves public speaking, blogging and training others to use Microsoft products. Before co-founding TSInfo Technologies, he was working with small and large organizations in various SharePoint On-premises as well as SharePoint Online office 365 & various related technologies. Bijaya also likes to publish SharePoint videos on his EnjoySharePoint YouTube Channel.

Learn AI & Machine Learning from the first principles. Key Features Explore how different industries are using AI and ML for diverse use-cases. Learn core concepts of Data Science, Machine Learning, Deep Learning and NLP in an easy and intuitive manner. Cutting-edge coverage on use of ML for business products and services. Explore how different companies are monetizing AI and ML technologies. Learn how you can start your own journey in the AI field from scratch. Description AI and machine learning (ML) are probably the most fascinating technologies of the 21st century. AI is literally in every industry now. From medical to climate change, education to sport, finance to entertainment, AI is disrupting every industry as we know. So, the basic knowledge of AI/ML becomes mandatory for everyone. This book is your first step to start the journey in this field. Along with basic concepts of fields, like machine learning, deep learning and NLP, we will also explore how big companies are using these technologies to deliver greater user experience and earning millions of dollars in profit. Also, we will see how the owners of small- or medium-sized businesses can leverage and integrate these technologies with their products and services. Leveraging AI and ML can become that competitive moat which can differentiate the product from others. In this book, you will learn the root concepts of AI/ML and how these inanimate machines can actually become smarter than the humans at a few tasks, and how companies are using AI and how you can leverage AI to earn profits. What you will learn Core concepts of data science, machine learning, deep learning and NLP in simple and intuitive words How you can leverage and integrate AI technologies in your business to differentiate your product in the market. The limitations of traditional non-tech businesses and how AI can bridge those gaps to increase revenues and decrease costs. How AI can help companies in launching new products, improving existing ones and automating mundane processes. Explore how big tech companies are using AI to automate different tasks and providing unique product experiences to their users. Who this book is for This book is for anyone who is curious about this fascinating technology and how it really works at its core. It is also beneficial to those who want to start their career in AI/ ML. Table of Contents 1.Introduction 2. Going deeper in ML concepts 3. Business perspective of AI 4. How to get started and pitfalls to avoid About the Authors Prashant Kikani is an experienced data scientist, who ranks in the top 1% worldwide in competitions and kernels on Kaggle which is the world's largest community and platform for data science and machine learning. As part of his day-to-day work, he is working on solving some of the hardest problems for the human kind, like language translation using state-of-the-art deep learning-based NLP models and infusion of knowledge graphs in NLP models. He is one of the youngest students to achieve the Master title on the Kaggle kernel platform. Also, he has worked on other deep learning sub-fields like computer vision via Kaggle competitions. His interests lie in AI/ML and deep learning, and teaching others what he has learned in a very simple and intuitive manner. This book is part of his interest to share his knowledge in the simplest possible manner with everyone so that everyone they can learn about this fascinating technology called AI! Blog links:http://prashantkikani.com LinkedIn Profile://https://www.linkedin.com/in/prashant-kikani/

Best Book on GAN Key Features Understanding the deep learning landscape and GAN’s relevance Learning basics of GAN Learning how to build GAN from scratch Understanding mathematics and limitations of GAN Understanding GAN applications for Retail, Healthcare, Telecom, Media and EduTech Understanding the important GAN papers such as pix2pixGAN, styleGAN, cycleGAN, DCGAN Learning how to build GAN code for industrial applications Understanding the difference between varieties of GAN Description This book aims at simplifying GAN for everyone. This book is very important for machine learning engineers, researchers, students, professors, and professionals. Universities and online course instructors will find this book very interesting for teaching advanced deep learning, specially Generative Adversarial Networks(GAN). Industry professionals, coders, and data scientists can learn GAN from scratch. They can learn how to build GAN codes for industrial applications for Healthcare, Retail, HRTech, EduTech, Telecom, Media, and Entertainment. Mathematics of GAN is discussed and illustrated. KL divergence and other parts of GAN are illustrated and discussed mathematically. This book teaches how to build codes for pix2pix GAN, DCGAN, CGAN, styleGAN, cycleGAN, and many other GAN. Machine Learning and Deep Learning Researchers will learn GAN in the shortest possible time with the help of this book. What will you learn Machine Learning Researchers would be comfortable in building advanced deep learning codes for Industrial applications Data Scientists would start solving very complex problems in deep learning Students would be ready to join an industry with these skills Average data engineers and scientists would be able to develop complex GAN codes to solve the toughest problems in computer vision Who this book is for This book is perfect for machine learning engineers, data scientists, data engineers, deep learning professionals and computer vision researchers. This book is also very useful for medical imaging professionals, autonomous vehicles professionals, retail fashion professionals, media & entertainment professional, edutech and HRtech professionals. Professors and Students working in machine learning, deep learning, computer vision and industrial applications would find this book extremely useful. Table of Contents 1 Basics of GAN 2 Introduction 3 Problem with GAN 4 Famous Types Of GANs About the Author Navin K Manaswi has been developing AI solutions/products for HRTech, Retail, ITSM, Healthcare, Telecom, Insurance, Digital Marketing, and Supply Chain while working for Consulting companies in Malaysia, Singapore, and Dubai . He is a serial entrepreneur in Artificial Intelligence and Augmented Reality Space. He has been building solutions for video intelligence, document intelligence, and human-like chatbots. He is Guest Faculty at IIT Kharagpur for AI Course and an author of the famous book on deep learning. He is officially a Google Developer Expert in machine learning. He has been organizing and mentoring AI hackathons and boot camps at Google events and college events. His startup WoWExp has been building awesome products in AI and AR space. Your Blog links: www.navinmanaswi.com Your LinkedIn Profile: https://www.linkedin.com/in/navin-manaswi-1a708b8/

Learn, develop, test and document powerful yet simple RAML API specifications using MuleSoft API Designer and API Toolkit. Key Features Explore concept of API and its significance in enterprise applications Design your own API using Mulesoft Anypoint Platform Exciting coverage on how API works in Enterprise Applications Live demonstration on how to build and integrate API with end-to-end implementation and working code Description Hands-on MuleSoft Anypoint platform book directs you step-by-step in designing API, its Implementation, and how to integrate smartly with other applications. This book is enriched with lots of interactive screenshots and working source codes. Throughout this book, you will learn key industry insights on System Integration, API Led Connectivity, Centre for Enablement, and RAML. This book will talk about how to use publicly available free mock REST APIs and how to call and test them from RESTful clients like Postman. You can also see some of the commercially available license-based APIs. Equipped with exercises, you will practice developing your own RESTful API specification along with how to add, retrieve, update, and delete data for your business use. You will be using the MuleSoft Anypoint Platform Designer for designing and simulating your RAML API design specifications. At the end of the book, you will be summarizing your learnings with an end-to-end implementation demonstration on the API design and its implementation. What you will learn Know-how of public APIs, commercial APIs, and cloud-based SaaS APIs Role of Mulesoft in SaaS applications You learn to design and test the API development and implementation You get handy with all the features and mechanism of Mulesoft Anypoint Platform Who this book is for This book is for fresher, IT employees with less or no programming background such as Business Analysts, Quality Engineers, HR, Technical persons who are looking for a change in technology area if they are working in outdated technologies. Table of Contents 1. MuleSoft Fundamentals 2. MuleSoft Internals 3. MuleSoft Salient features 4. From ESB to API Led Connectivity 5. Cloud based SaaS Applications and MuleSoft Connectors 6. REST, SOAP, Postman and Anypoint Studio 7. Start RAML 8. RAML in detail 9. RAML Project About the Authors Nanda Nachimuthu is an Engineering graduate from Tamilnadu Agricultural University, Coimbatore, and Tamilnadu and has done Advanced Diploma from Indian Institute of Technology, Kharagpur in the field of Java and Internet Computing. He has also completed an Advanced Diploma from Indian Institute of International Trading, Delhi which specializes on Strategies for International Business. His 25 years of experience comes from various domains like Banking, Healthcare, Government and Airlines. He is, in to the technologies like Java, Big Data, Cloud, ESB, Security and IoT. He played various roles like Technical Architect, Solutions Architect, Cloud Architect and Enterprise Integration Architect and wanted to be in an Individual Contributor role always with hands-on coding experience. He is passionate about Social Entrepreneurship and Pro Bono consultations in multiple fields like Information Technology, Manufacturing, Trading, Agriculture and Internet of Things. He is the founder of some social platforms, and he owns few trademarks under his kitty. Presently he is focusing on Integration Technology Platforms like MuleSoft, where he finds lots of scope in the future for Digital Marketing and Machine to Machine Communications. LinkedIn Profile: https://www.linkedin.com/in/nanda3008/ Github: https://github.com/nanda3008

Hands-on MuleSoft Flows using MuleSoft Anypoint Studio Components and understanding Payload processing along with debugging. Key Features Get familiar with the MuleSoft Anypoint Studio key techniques such as Payload, Logger, Variables, Flow and Flow Reference. Deep dive into Massage Structure and Payload value handling. Get familiar with the Global Configuration Properties and Securing properties. Explore Mule Run Time and Deploying Mule Projects in CloudHub. Description This book is aimed to teach the readers how to design RAML APIs using Anypoint Platform. It also focuses on popular topics such as System Integration, API Led Connectivity, and Centre for Enablement and RAML. It will show how to use, call and test free mock REST APIs. The readers can also work with some commercially available license-based APIs. Furthermore, the book will explain most of the examples provided by RAML.org so that you can simulate it from your local system. This book will then help you develop your RESTful API specification for adding, retrieving, updating and deleting data for a business entity. Later, you will learn how to use the MuleSoft Anypoint Platform Designer for designing and simulating your RAML API design specifications. By the end, you will be able to develop an end to end RAML API using the MuleSoft Anypoint Studio. What you will learn Get exposed to Payload handling, logging and variables Work with different Flow Control components such as Choice, First Successful, Round-Robin and Scatter Gather Explore and work with Error Handling components such as Error Handler, On Error, Continue, On Error Propagate and Raise Error Understand Global Configuration Properties and Securing properties Gain knowledge about various scopes involved in MuleSoft Flow designing Who this book is for This book is meant for anyone interested to become an API designer. Experienced technical persons of the IT industry also can utilize the book to get extra insights, and they can align their knowledge in line with it. Table of Contents 1. Start Project 2. Anypoint Studio Components 3. Flow Control Components 4. Idempotent, Parse Template and Scheduler 5. Payload Component 6. MUnit 7. MuleSoft Runtime 8. Global Secured Configurations 9. Error Handling 10. RAML and Anypoint Studio About the Authors Nanda Nachimuthu is an Engineering graduate from Tamil Nadu Agricultural University, Coimbatore, and has completed Advanced Diploma from the Indian Institute of Technology, Kharagpur, in the field of Java and Internet Computing. He has also completed an Advanced Diploma from Indian Institute of International Trading, Delhi, which specializes in Strategies for International Business. He has 25 years of experience in various domains like banking, healthcare, government, and airlines. He’s into technologies like Java, Big Data, Cloud, ESB, Security and IoT. He has taken up various roles like technical architect, solutions architect, cloud architect, and enterprise integration architect and always wanted to take up an individual contributor’s role with hands-on coding experience. He is passionate about social entrepreneurship and takes pro-bono consultations in multiple fields like information technology, manufacturing, trading, agriculture, and internet of things. The founder of some social platforms, he also has a few trademarks under his kitty. Presently, he is focusing on integration technology platforms like MuleSoft, where he finds a wide scope in the future for digital marketing and machine to machine communication. Github Link: github.com/nanda3008 LinkedIn Profile: https://www.linkedin.com/in/nanda3008/

Step-by-step guide to learn and solve complex computational problems with Nature Inspired algorithms. Key Features Artificial Neural Networks Deep Learning models using Keras Quantum Computers and Programming Genetic Algorithms, CNN and RNNs Swarm Intelligence Systems Reinforcement Learning using OpenAI Artificial Life DNA computing Fractals Description Natural Computing is the field of research inspired by nature, that allows the development of new algorithms to solve complex problems, leads to the synthesis of natural models, and may result in the design of new computing systems. This book exactly aims to educate you with practical examples on topics of importance associated with research field of Natural computing. The initial few chapters will quickly walk you through Neural Networks while describing deep learning architectures such as CNN, RNN and AutoEncoders using Keras. As you progress further, you’ll gain understanding to develop genetic algorithm to solve traveling saleman problem, implement swarm intelligence techniques using the SwarmPackagePy and Cellular Automata techniques such as Game of Life, Langton's ant, etc. The latter half of the book will introduce you to the world of Fractals such as such as the Cantor Set and the Mandelbrot Set, develop a quantum program with the QiSkit tool that runs on a real quantum computing platform, namely the IBM Q Machine and a Python simulation of the Adleman experiment that showed for the first time the possibility of performing computations at the molecular level. What You Will Learn Mastering Artificial Neural Networks Developing Artificial Intelligence systems Resolving complex problems with Genetic Programming and Swarm intelligence algorithms Programming Quantum Computers Exploring the mathematical world of fractals Simulating complex systems by Cellular Automata Understanding the basics of DNA computation Who This Book Is For This book is for all science enthusiasts, in particular who want to understand what are the links between computer sciences and natural systems. Interested readers should have good skills in math and python programming along with some basic knowledge of physics and biology. . Although, some knowledge of the topics covered in the book will be helpful, it is not essential to have worked with the tools covered in the book. Table of Contents Neural Networks Deep Learning Genetic Programming Swarm Intelligence Cellular Automata Fractals Quantum Computing DNA Computing About the Author Giancarlo Zaccone has over ten years of experience in managing research projects in scientific and industrial areas. He is a Software and Systems Engineer Consultant at European Space Agency (ESTEC). Giancarlo holds a master’s degree in Physics and an advanced master’s degree in Scientific Computing at La Sapienza of Rome. His LinkedIn Profile: https://www.linkedin.com/in/giancarlozaccone/

Learn how to work towards making the most out of a career in emerging tech Key Features Understand the core concepts related to careers in emerging tech. Learn innovative, exclusive, and exciting ways to design a successful career in ET. Reduce your learning curve by examining the career trajectories of eminent ET professionals. Ways to evolve and adapt to changing ET paradigms. Practical perspective from the field. Description Cracking the emerging tech code will help you attain your Emerging Technology (ET) career goals faster without spending years in committing avoidable mistakes, recovering from them, and learning things the hard way. You can apply practical tips in areas such as improving your ability to craft market-friendly use cases and evolving a solution approach in new and diverse tech or business environments, to propel forward your career in strategic and proactive ways. It outlines ways in which you can explore and capitalize on hidden opportunities while working on important career aspects. The anecdotes and solutions provided will aid you in getting an inside out view to reduce your learning curve. This book will help you in gaining both magnitude and direction in your ET career journey and prevent you from getting overwhelmed or pinned down by the forces of ET. Authored by an ET professional, this book will take you through a series of steps to deepen your understanding of the forces that shape one’s ET career and successfully dealing with them. It also helps bust myths, addresses fallacies, and common misconceptions that could harm one’s career prospects. There are also practical and easy-to-adopt tips, methods, tracking mechanisms, and information that will improve career standing and professional growth. This book makes it easy for you to enhance your employability and job market relevance so that you can sprint towards a rewarding career. What will you learn Through this book, you will connect with ways and means to build a strong and rewarding emerging tech career. You will be able to work on identifying the right technology and employer, enhancing employability and differentiation in the job market, addressing challenges and connecting with enablers, accurate growth strategies and execution principles. Who this book is for This book is for current and aspiring emerging tech professionals, students, and anyone who wishes to understand ways to have a fulfilling career in emerging technologies such as AI, blockchain, cybersecurity, IoT, space tech, and more. Table of Contents 1. Introduction 2. The best ET for me and some myth bursting 3. Getting prepared and charting a roadmap 4. Identifying the requirements and getting help 5. Dealing with headwinds and drawing a career change action plan 6. Building an ET friendly résumé and finding the right employer 7. Getting hired through social media 8. Job search 9. Impressing the emerging tech jury 10. The secret sauce 11. Becoming a thought leader 12. Measuring success and making course corrections 13. Drawing the two-year plan 14. Building your leadership capabilities 15. To start-up or not? 16. Communications skills: getting it right 17. Building a personal brand 18. Post-script About the Authors Prayukth has been actively involved in productizing and promoting cross eco-system collaboration in the IoT space for over half-a-decade. In recent years, he has focused on exposing APT groups, global footprint, and in evaluating the evolving threat landscape surrounding IoT and OT environments. In his current role, he has taken Subex’s IoT business to new geographies. Your Linkedin profile: https://www.linkedin.com/in/prayukthkv/